class_docstr: Base class for op benchmarks.
docstr: Transforms the text batch inputs to a ragged shape.
docstr_tok: ["Transforms","the","text","batch","inputs","to","a","ragged","shape","."]
code: def _convert_to_ragged_inputs(self, inputs):
      """Transforms the text batch inputs to a ragged shape."""
      if isinstance(self.input_data, ragged_tensor.RaggedTensor):
          return inputs
  
      inputs = text_ops.WhitespaceTokenizer().tokenize(inputs)
      return inputs
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import time
  import tensorflow
  import tensorflow_datasets
  from tensorflow.python.client import session
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import lookup_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow_text.python import ops
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 5 for calling the OpsBaseBenchmark obj's underlying member method code with example usage: obj._convert_to_ragged_inputs(inputs) and returns: inputs, inputs